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Support vector machine Performance for: CIIE 2018 folio number 2018062802133: A Computational Literature Review of Educational Innovation'
Support vector machine Performance for: CIIE 2018 folio number 2018062802133: A Computational Literature Review of Educational Innovation'
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Zenodo
2018-12-11 更新
2026-04-07 收录
教育文献分类
SVM分类性能
数据链接：
https://zenodo.org/record/2214581
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资源简介：
Results of support vector machine classification.
应用场景：
提供机构：
Mario
创建时间：
2018-12-11
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SVM classification accuracy scores.
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Accuracy values for SVM classification, provided as a CSV file with comma-separated values. (CSV)
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Comparison of classification performance of SVM Models on different feature sets.
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Comparison of classification performance of SVM Models on different feature sets.
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SVM Classification Results for five different kernels for Test v/s Background1 (Variance Reduced).
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Performance of SVM based models using dipeptide composition as input feature on whole peptide dataset and nine terminus datasets.
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Sn: Sensitivity; Sp: Specificity; Acc: Accuracy; MCC: Matthew’s Correlation Coefficient. Performance of SVM based models using dipeptide composition as input feature on whole peptide dataset and nine
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Classification Report of the SVM classifier without using any window.
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Classification Report of the SVM classifier without using any window.
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